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Laboratory Implementation of Direct Torque Controller based Speed Loop Pseudo Derivative Feedforward Controller for PMSM Drive

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CES Transactions on Electrical Machines and Systems 2024年第1期8卷 12-21页

作者： prabhakaran Koothu Kesavan Umashankar Subramaniam Dhafer J.Almakhles IEEE Renewable Energy Laboratory Department of Electrical EngineeringPrince Sultan UniversityRiyadh 12435Saudi Arabia

This paper,evaluate the effectiveness of a proposed speed loop pseudo derivative feedforward(PDFF)controller-based direct torque controller(DTC)for a PMSM drive against the performance of existing PI speed controller-based DTC and hysteresis current controller(HCC).The proposed PDFF-based speed regulator effectively reduces oscillation and overshoot associated with rotor angular speed,electromagnetic torque,and stator current.Two case studies,one using forward-to-reverse motoring operation and the other involving reverse-to-forward braking operation,has been validated to show the effectiveness of the proposed control strategy.The proposed controller's superior performance is demonstrated through experimental verification utilizing an FPGA controller for a 1.5 kW PMSM drive laboratory prototype.

关键词： Direct torque control Pseudo derivative feedforward controller Permanent magnet synchronous motor(PMSM)

Heavy metal pollution of river water and eco-friendly remediation using potent microalgal species

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Water Science and Engineering 2024年第1期17卷 41-50页

作者： Amudham Radha Amal Raj prabhakaran Mylsamy V.Sivasankar B.Sathish Kumar Kiyoshi Omine T.G.Sunitha Phycological Research Laboratory Research Department of BotanyPachaiyappa's College(Affliated to University of Madras)Chennai 600030India Research Department of Chemistry Pachaiyappa's College(Affliated to University of Madras)Chennai 600030India Department of Botany Sri Vidya Mandir Arts&Science College(Autonomous)KatteriUthangarai 636902India Department of Civil Engineering School of Engineering.Nagasaki UniversityNagasaki-Daigaku1-14 Bunkyo-machiNagasaki 8528521Japan

Pollution of rivers is mainly caused by anthropogenic activities such as discharge of effluent from industrial facilities,maintenance of sewage/effluent treatment plants,and dumping of solid waste on river banks.This study dealt with the pollution issues of the Cooum River in the well-known city of Chennai in South India.Water samples from 27 locations were collected and analyzed for 12 elements,including Ba,B,and Al,as well as heavy metals such as Pb,Cr,Mn,Fe,Co,Ni,Cu,Zn,and Cd.The samples showed levels of these elements that exceeded World Health Organization recommendations.Pearson correlation analysis revealed the inter-dependency among elements,and the contribution of each element based on factor loadings showed its percentage contribution compared to others.Water samples from six significant locations were chosen for remediation with three algae:Chlorella vulgaris,Scenedesmus dimorphus,and Phormedium sp.The uptake of pollutants led to the continuous growth of algae during the incubation period of 15 d,effectively removing heavy metals from the river water.The increasing levels of algal counts and the chlorophyll a content confirmed the algal growth during the incubation period,followed by a declining stage after the incubation period.The scanning electron microscopic images of algae before and after the remediation showed no remarkable modification of morphological patterns.This study showed that the uptake of heavy metals using algae is an effective water pollution remediation measure,making the process practicable in the field on a large scale in the near future.

关键词： Heavy metal Cooum river Phycoremediation Microalgae Factor analysis

Single-stage PV-powered boost inverter-fed permanent-magnet synchronous motor-driven water-pumping system

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Clean Energy 2022年第5期6卷 726-737页

作者： K.K.prabhakaran Varsha Sunkara A.Karthikeyan Department of Electrical and Electronics Engineering National Institute of Technology KarnatakaSurathkalIndia

In this paper,a photovoltaic(PV)fed boost inverter-based permanent-magnet synchronous motor(PMSM)-driven water-pumping system for stand-alone applications is proposed.The proposed system comprises PV panel,six switches,three inductors(L),three capacitors(C)and a water pump.In this work,the boost inverter is designed with a gain of two and thereby the direct current input required to run the motor is considerably reduced.Hence,the size of the system is reduced.The voltage gain factor depends upon the placement of the L and C components and their values.The speed reference is generated using a perturb and observe maximum power point tracking algorithm.Vector control is employed to control a boost inverter-fed PMSM drive.The proposed system is simulated using a MATLAB®/Simulink®environment and experimental validation is performed on a PMSM laboratory prototype using a field programmable gate array controller.The simulation and experimental results demonstrate the effectiveness of the proposed system.

关键词： boost inverter MPPT PV PMSM water pump

Deep Learning-Based Model for Defect Detection and Localization on Photovoltaic Panels

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Computer Systems Science & Engineering 2023年第3期44卷 2683-2700页

作者： S.prabhakaran R.Annie Uthra J.Preetharoselyn Department of Computational Intelligence SRM Institute of Science and TechnologyChengalpattu603203India Department of Electrical Engineering SRM Institute of Science and TechnologyChengalpattu603203India

The Problem of Photovoltaic(PV)defects detection and classification has been well studied.Several techniques exist in identifying the defects and localizing them in PV panels that use various features,but suffer to achieve higher performance.An efficient Real-Time Multi Variant Deep learning Model(RMVDM)is presented in this article to handle this issue.The method considers different defects like a spotlight,crack,dust,and micro-cracks to detect the defects as well as loca-lizes the defects.The image data set given has been preprocessed by applying the Region-Based Histogram Approximation(RHA)algorithm.The preprocessed images are applied with Gray Scale Quantization Algorithm(GSQA)to extract the features.Extracted features are trained with a Multi Variant Deep learning model where the model trained with a number of layers belongs to different classes of neurons.Each class neuron has been designed to measure Defect Class Support(DCS).At the test phase,the input image has been applied with different operations,and the features extracted passed through the model trained.The output layer returns a number of DCS values using which the method identifies the class of defect and localizes the defect in the image.Further,the method uses the Higher-Order Texture Localization(HOTL)technique in localizing the defect.The pro-posed model produces efficient results with around 97%in defect detection and localization with higher accuracy and less time complexity.

关键词： Photovoltaic systems deep learning defect detection classification localization

Feature Extraction and Classification of Photovoltaic Panels Based on Convolutional Neural Network

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Computers, Materials & Continua 2023年第1期74卷 1437-1455页

Photovoltaic(PV)boards are a perfect way to create eco-friendly power from daylight.The defects in the PV panels are caused by various conditions;such defective PV panels need continuous monitoring.The recent development of PV panel monitoring systems provides a modest and viable approach to monitoring and managing the condition of the PV plants.In general,conventional procedures are used to identify the faulty modules earlier and to avoid declines in power generation.The existing deep learning architectures provide the required output to predict the faulty PV panels with less accuracy and a more time-consuming process.To increase the accuracy and to reduce the processing time,a new Convolutional Neural Network(CNN)architecture is required.Hence,in the present work,a new Real-time Multi Variant Deep learning Model(RMVDM)architecture is proposed,and it extracts the image features and classifies the defects in PV panels quickly with high accuracy.The defects that arise in the PV panels are identified by the CNN based RMVDM using RGB images.The biggest difference between CNN and its predecessors is that CNN automatically extracts the image features without any help from a person.The technique is quantitatively assessed and compared with existing faulty PV board identification approaches on the large real-time dataset.The results show that 98%of the accuracy and recall values in the fault detection and classification process.

关键词： Photovoltaic panels deep learning defect feature extraction RMVDM

A Review on Challenges in DC Microgrid Planning and Implementation

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Journal of Modern Power Systems and Clean Energy 2023年第5期11卷 1375-1395页

作者： Kolampurath Jithin Puthan Purayil Haridev Nanappan Mayadevi Raveendran Pillai Harikumar Valiyakulam prabhakaran Mini IEEE Department of Electrical Engineering College of Engineering TrivandrumAPJ Abdul Kalam Technological University(APJAKTU)ThiruvananthapuramKeralaIndia Tata Consultancy Services(TCS) KochiKeralaIndia

DC microgrids are gaining more attention with the increased penetration of various DC sources such as solar photovoltaic systems, fuel cells, batteries, etc., and DC loads. Due to the rapid integration of these components into the existing power system, the importance of DC microgrids has reached a salient point. Compared with conventional AC systems, DC systems are free from synchronization issues, reactive power control, frequency control, etc., and are more reliable and efficient.However, many challenges need to be addressed for utilizing DC power to its full potential. The absence of natural current zero is a significant issue in protecting DC systems. In addition,the stability of the DC microgrid, which relies on inertia, needs to be considered during system design. Moreover, power quality and communication issues are also significant challenges in DC microgrids. This paper presents a review of various value streams of DC microgrids including architectures, protection schemes, power quality, inertia, communication, and economic operation. In addition, comparisons between different microgrid configurations, the state-of-the-art projects of DC microgrid, and future trends are also set forth for further studies.

关键词： Architecture communication DC microgrid economic operation inertia protection power quality

Modelling and Coordinated Control of Grid Connected Photovoltaic,Wind Turbine Driven PMSG,and Energy Storage Device for a Hybrid DC/AC Microgrid

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Protection and Control of Modern Power Systems 2023年第1期8卷 180-193页

作者： prabhakaran Koothu Kesavan Umashankar Subramaniam Dhafer Jaber Almakhles Sivakumar Selvam Renewable Energy Laboratory the Department of Electrical EngineeringPrince Sultan UniversityRiyadh11586Saudi Arabia 不详

In a DC/AC microgrid system,the issues of DC bus voltage regulation and power sharing have been the subject of a significant amount of research.Integra-tion of renewable energy into the grid involves multiple converters and these are vulnerable to perturbations caused by transient events.To enhance the flexibility and controllability of the grid connected converter(GCC),this paper proposes a common DC bus voltage maintenance and power sharing control strategy of a GCC for a DC/AC microgrid.A maximum power point tracking algorithm is employed to enhance the power delivered by the wind turbine and photovoltaic module.The proposed control strategy consists of primary and secondary as-pects.In the primary layer control,the DC bus voltage is regulated by the GCC.In the secondary layer,the DC bus voltage is maintained by the energy storage device.This ensures reliable power for local loads during grid failures,while power injection to the grid is controlled by an en-ergy management algorithm followed by reference gen-eration of inductor current in the GCC.The proposed control strategy operates in different modes of DC voltage regulation,power injection to the grid and a hybrid op-erating mode.It provides wide flexible control and en-sures the reliable operation of the microgrid.The pro-posed and conventional techniques are compared for a 15.8 kW DC/AC microgrid system using the MATLAB/Simulink environment.The simulation results demonstrate the transient behaviour of the system in different operating conditions.The proposed control technique is twice as fast in its transient response and produces less oscillation than the conventional system.Index Terms—Wind energy,photovoltaic energy,DC/AC microgrid,battery energy storage system,co-ordinated control.

关键词： Wind energy photovoltaic energy DC/AC microgrid battery energy storage system co-ordinated control

Atomic Heterointerface Engineering of Nickel Selenide Confined Nickel Molybdenum Nitride for High-Performance Solar-Driven Water Splitting

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Energy & Environmental Materials 2023年第2期6卷 397-407页

作者： Jingqiang Wang Duy Thanh Tran Kai Chang Sampath prabhakaran Do Hwan Kim Nam Hoon Kim Joong Hee Lee Department of Nano Convergence Engineering Jeonbuk National UniversityJeonjuJeonbuk 54896Korea Division of Science Education Graduate School of Department of Energy Storage/Conversion EngineeringJeonbuk National UniversityJeonjuJeonbuk 54896Korea Carbon Composite Research Center Department of Polymer-Nano Science and TechnologyJeonbuk National UniversityJeonjuJeonbuk 54896Korea

A heterostructured electrocatalyst of small NiSe_(2) nanoparticles confined NiMoN nanorods(NiSe_(2)-NPs/NiMoN-NRs)is prepared to accelerate both the hydrogen evolution reaction(HER)and oxygen evolution reaction(OER)in a same alkaline medium.The synergistic effects caused by the combination of merits derived from NiSe_(2) and NiMoN phases trigger an optimum electronic structure with high density of state at near Fermi level and enhance adsorption free energy,thereby resulting in excellent catalytic activities and strengthened working stability.The catalyst requires a low overpotential of 58 mV for HER and 241 mV for OER to reach 10 mA cm^(−2) in 1.0 M KOH electrolyte.A twoelectrode electrolyzer based on the developed catalyst shows outstanding cell voltage of 1.51 and 1.46 V to reach 10 mA cm^(−2) in 1.0 M and 30 wt%KOH solution at 25℃ for overall water splitting,respectively.In addition,the solardriven water splitting process delivers a high solar-to-H_(2) conversion efficiency of∼18.4%,impressively unveiling that the developed bifunctional catalyst is highly potential for overall water splitting to produce green hydrogen fuel.

关键词： Bifunctional electrocatalyst Novel NiSe_(2)/NiMoN heterostructures Solardriven water splitting Synergistic effects

Study of engineering electronic structure modulated non-noble metal oxides for scaled-up alkaline blend seawater splitting

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Journal of Energy Chemistry 2023年第11期86卷 167-179,I0004页

作者： Natarajan Logeshwaran Subramanian Vijayapradeep Ae Rhan Kim prabhakaran Sampath Shanmugam Ramakrishnan Milan Babu Poudel Do Hwan Kim Dong Jin Yoo Graduate School Department of Energy Storage/Conversion Engineering(BK21 FOUR)Hydrogen and Fuel Cell Research CenterJeonbuk National University567-Baekje-daeroDeokjin-guJeonju-siJeollabuk-do 54896Republic of Korea Department of Life Science Jeonbuk National University567-Baekje-daeroDeokjin-guJeonju-siJeollabuk-do 54896Republic of Korea Division of Science Education and Institute of Fusion Science Jeonbuk National University567-Baekje-daeroDeokjin-guJeonju-siJeollabuk-do 54896Republic of Korea Department of Nano Convergence Engineering Jeonbuk National University567-Baekje-daeroDeokjin-guJeonju-siJeollabuk-do 54896Republic of Korea School of Engineering Merz CourtNewcastle UniversityNE17RUUnited Kingdom

Scaled-up industrial water electrolysis equipment that can be used with abundant seawater is key for affordable hydrogen production.The search for highly stable,dynamic,and economical electrocatalysts could have a significant impact on hydrogen commercialization.Herein,we prepared energy-efficient,scalable,and engineering electronic structure modulated Mn-Ni bimetal oxides(Mn_(0.25)Ni_(0.75)O)through simple hydrothermal followed by calcination method.As-optimized Mn_(0.25)Ni_(0.75)O displayed enhanced oxygen and hydrogen evolution reaction(OER and HER)performance with overpotentials of 266 and115 mV at current densities of 10 mA cm^(-2)in alkaline KOH added seawater electrolyte solution.Additionally,Mn-Ni oxide catalytic benefits were attributed to the calculated electronic configurations and Gibbs free energy for OER,and HER values were estimated using first principles calculations.In real-time practical application,we mimicked industrial operating conditions with modified seawater electrolysis using Mn_(0.25)Ni_(0.75)O‖Mn_(0.25)Ni_(0.75)O under various temperature conditions,which performs superior to the commercial IrO_(2)‖Pt-C couple.These findings demonstrate an inexpensive and facile technique for feasible large-scale hydrogen production.

关键词： Waterel ectrolysis Mn-Ni oxide complex Chlorine evolution reaction Industrial seawater operations Density functional theory calculations